Paper Info
Title
Deciphering Key Genes and miRNAs Associated With Hepatocellular Carcinoma via Network-Based Approach
Abstract
AbstractHepatocellular carcinoma (HCC)is a common type of liver cancer and has a high mortality world-widely. The diagnosis, prognoses, and therapeutics are very poor due to the unclear molecular mechanism of progression of the disease. To unveil the molecular mechanism of progression of HCC, we extract a large sample of mRNA expression levels from the GEO database where a total of 167 samples were used for study, and out of them, 115 samples were from HCC tumor tissue. This study aims to investigate the module of differentially expressed genes (DEGs)which are co-expressed only in HCC sample data but not in normal tissue samples. Thereafter, we identified the highly significant module of significant co-expressed genes and formed a PPI network for these genes. There were only six genes (namely, MSH3, DMC1, ALPP, IL10, ZNF223, and HSD17B7)obtained after analysis of the PPI network. Out of six only MSH3, DMC1, HSD17B7, and IL10 were found enriched in GO Term & Pathway enrichment analysis and these candidate genes were mainly involved in cellular process, metabolic and catalytic activity, which promote the development & progression of HCC. Lastly, the composite 3-node FFL reveals the driver miRNAs and TFs associated with our key genes.
Year
DOI
Venue
2022
10.1109/TCBB.2020.3016781
IEEE/ACM Transactions on Computational Biology and Bioinformatics
Keywords
DocType
Volume
Cancer, Gene expression, Liver, Electronic mail, Tumors, Hepatocellular carcinoma, module selection, gene co-expression network, miRNA, PPI
Journal
19
Issue
ISSN
Citations 
2
1545-5963
0
PageRank 
References 
Authors
0.34
0
8
Name
Order
Citations
PageRank
Sachin Bhatt100.34
Prithvi Singh200.34
archana sharma3131.54
Arpita Rai400.34
Ravins Dohare521.39
Shweta Sankhwar622.04
Akash Sharma700.34
Mansoor Ali Syed800.34